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Development and validation of an MRI-based radiomic signature for the preoperative prediction of treatment response in patients with invasive functional pituitary adenoma.
- Source :
-
European journal of radiology [Eur J Radiol] 2019 Dec; Vol. 121, pp. 108647. Date of Electronic Publication: 2019 Sep 07. - Publication Year :
- 2019
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Abstract
- Purpose: The preoperative prediction of treatment response is important for determining individual treatment strategies for invasive functional pituitary adenoma (IFPA). This study aimed to develop and validate a magnetic resonance imaging (MRI)-based radiomic signature for preoperative prediction of treatment response in IFPA.<br />Method: One hundred and sixty-three patients with IFPA were enrolled and divided into primary (n = 108) and validation cohorts (n = 55) according to time point. IFPA patients were divided into remission and non-remission according to postoperative hormone levels. Radiomic features were extracted from their MR images and a radiomic signature was built using a support vector machine. Subsequently, multivariable logistic regression analysis was used to select the most informative clinical features, and a radiomic model incorporating the radiomic signature and selected clinical features was constructed and used as the final predictive model.<br />Results: Seven radiomic features were selected to construct the radiomic signature, which achieved an area under the curve (AUC) of 0.834 and 0.808 on the primary and validation cohorts respectively. The radiomic model incorporating the radiomic signature and Knosp grade showed good discrimination abilities and calibration, with AUCs of 0.832 and 0.811 for the primary and validation cohorts respectively. The radiomic signature and radiomic model better estimated the treatment responses of patients with IFPA than our clinical features model. Decision curve analysis showed the radiomic model was clinically useful.<br />Conclusions: This radiomic model may help neurosurgeons predict the treatment responses of patients with IFPA before surgery and determine individual treatment strategies.<br /> (Copyright © 2019 Elsevier B.V. All rights reserved.)
- Subjects :
- Adult
Area Under Curve
Female
Humans
Male
Pituitary Gland diagnostic imaging
Pituitary Gland surgery
Predictive Value of Tests
Reproducibility of Results
Retrospective Studies
Support Vector Machine
Treatment Outcome
Adenoma diagnostic imaging
Adenoma surgery
Magnetic Resonance Imaging methods
Pituitary Neoplasms diagnostic imaging
Pituitary Neoplasms surgery
Preoperative Care methods
Subjects
Details
- Language :
- English
- ISSN :
- 1872-7727
- Volume :
- 121
- Database :
- MEDLINE
- Journal :
- European journal of radiology
- Publication Type :
- Academic Journal
- Accession number :
- 31561943
- Full Text :
- https://doi.org/10.1016/j.ejrad.2019.108647